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From "Hudson (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAPREDUCE-5000) TaskImpl.getCounters() can return the counters for the wrong task attempt when task is speculating
Date Thu, 14 Feb 2013 13:06:15 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-5000?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13578339#comment-13578339
] 

Hudson commented on MAPREDUCE-5000:
-----------------------------------

Integrated in Hadoop-Hdfs-trunk #1316 (See [https://builds.apache.org/job/Hadoop-Hdfs-trunk/1316/])
    MAPREDUCE-5000. Fixes getCounters when speculating by fixing the selection of the best
attempt for a task. Contributed by Jason Lowe. (Revision 1445871)

     Result = FAILURE
sseth : http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1445871
Files : 
* /hadoop/common/trunk/hadoop-mapreduce-project/CHANGES.txt
* /hadoop/common/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-app/src/main/java/org/apache/hadoop/mapreduce/v2/app/job/impl/TaskImpl.java
* /hadoop/common/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-app/src/test/java/org/apache/hadoop/mapreduce/v2/app/job/impl/TestTaskImpl.java

                
> TaskImpl.getCounters() can return the counters for the wrong task attempt when task is
speculating
> --------------------------------------------------------------------------------------------------
>
>                 Key: MAPREDUCE-5000
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-5000
>             Project: Hadoop Map/Reduce
>          Issue Type: Bug
>          Components: mr-am
>    Affects Versions: 0.23.6
>            Reporter: Jason Lowe
>            Assignee: Jason Lowe
>            Priority: Critical
>             Fix For: 0.23.7, 2.0.4-beta
>
>         Attachments: MAPREDUCE-5000-branch-0.23.patch, MAPREDUCE-5000.patch
>
>
> When a task is speculating and one attempt completes then sometimes the counters for
the wrong attempt are aggregated into the total counters for the job.  The scenario looks
like this:
> # Two task attempts are racing, _0 and _1
> # _1 finishes first, causing the task to issue a TA_KILL to attempt _0
> # _0 receives TA_KILL, sets progress to 1.0f and waits for container cleanup
> # if TaskImpl.getCounters() is called now, TaskImpl.selectBestAttempt() can return _0
since it is not quite yet in the KILLED state yet progress is maxed out and no other attempt
has more progress.

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